In-vivo imaging of methionine metabolism in patients with suspected malignant pleural mesothelioma. Issue 11 (November 2019)

• Record Type: Journal Article
• Authors: Lopci, Egesta; Novellis, Pierluigi; Testori, Alberto; Rahal, Daoud; Voulaz, Emanuele; Bottoni, Edoardo; Ferraroli, Giorgio Maria; Crepaldi, Alessandro; Ceresoli, Giovanni Luca; Perrino, Matteo; Castello, Angelo; Alloisio, Marco; Veronesi, Giulia; Zucali, Paolo Andrea
• Is Part Of: Nuclear medicine communications. Volume 40:Issue 11(2019:Nov.)
• Publication Date: 2019-11
• Subjects: diagnosis -- malignant pleural mesothelioma -- methionine -- nodal involvement; Nuclear medicine -- Periodicals; 616.07575
• DOI: 10.1097/MNM.0000000000001078
• Languages: English
• ISSNs: 0143-3636

Abstract

Abstract : Objectives: In-vivo characterization of malignant pleural mesothelioma (MPM) with 11 C-methionine PET/computed tomography (MET PET). Methods: Between September 2014 and February 2016, 30 consecutive patients with clinical suspicion of MPM were prospectively recruited. The study was approved and registered at www.clinicaltrials.gov (NCT02519049). Patients were evaluated at baseline with MET PET (experimental) and fluorine-18 fluorodeoxyglucose PET/computed tomography (FDG PET) (standard). Principal parameters analyzed were SUVmax, SUVmean, metabolic tumor volume (MTV), and metabolic tumor burden (MTB = MTV ×SUVmean ). The reference standard for diagnostic performance was based on histology. Results: The presence of malignancy was confirmed in 29/30 patients: 23 (76.6%) with MPM (20 epithelioid, two biphasic, and one sarcomatoid), five (16.6%) with adenocarcinoma of the lung, and one (3.3%) with an undifferentiated carcinoma. In one case, diagnosis was benign pleural inflammation. All tumors showed increased uptake of 11 C-methionine: median SUVmax, SUVmean, MTV, and MTB were, respectively, 5.70 [95% confidence interval (CI): 4.51–6.79], 3.15 (95% CI: 2.71–3.40), 33.85 (95% CI: 14.08–66.64), and 105.25 (95% CI: 41.77–215.25). Pathology data revealed MTV and MTB to be significantly higher in nonepithelioid histology ( P < 0.05). The other parameters showed a homogeneous distribution across the tumor types. Overall, MET PET identified 49 lymph nodes, compared with 34 nodes on FDG PET, demonstrating a sensitivity of 91% (95% CI: 80–96%), a positive predictive value of 92% (95% CI: 82– 97%), and an accuracy of 85% ( P = 0.0042). Conclusions: MET PET is able to characterize MPM lesions regardless of histology. This technique shows higher sensitivity than FDG PET for the identification of secondary lymph nodes.